von der Haar, Tobias, Kazana, Eleanna (2014) The translational machinery is an optimized molecular network that affects cellular homoeostasis and disease. Biochemical Society Transactions, 42 (1). pp. 173-176. ISSN 0300-5127. (doi:10.1042/BST20130131) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:38182)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1042/BST20130131 |
Abstract
Translation involves interactions between mRNAs, ribosomes, tRNAs and a host of translation factors. Emerging evidence on the eukaryotic translational machinery indicates that these factors are organized in a highly optimized network, in which the levels of the different factors are finely matched to each other. This optimal factor network is essential for producing proteomes that result in optimal fitness, and perturbations to the optimal network that significantly affect translational activity therefore result in non-optimal proteomes, fitness losses and disease. On the other hand, experimental evidence indicates that translation and cell growth are relatively robust to perturbations, and viability can be maintained even upon significant damage to individual translation factors. How the eukaryotic translational machinery is optimized, and how it can maintain optimization in the face of changing internal parameters, are open questions relevant to the interaction between translation and cellular disease states.
Item Type: | Article |
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DOI/Identification number: | 10.1042/BST20130131 |
Uncontrolled keywords: | disease; protein synthesis; ribosome; robustness; translation |
Subjects: | Q Science > QP Physiology (Living systems) > QP506 Molecular biology |
Divisions: | Divisions > Division of Natural Sciences > Biosciences |
Depositing User: | Tobias von der Haar |
Date Deposited: | 07 Feb 2014 12:14 UTC |
Last Modified: | 05 Nov 2024 10:22 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/38182 (The current URI for this page, for reference purposes) |
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